GPT-J vs GPT-3 in Doctor.ai
For me, GPT-3 is still the one
In my previous articles, I have given lots of praise to GPT-3, a text generator from OpenAI. In my medical chatbot Doctor.ai, I used GPT-3 to convert English to Neo4j’s Cypher, translate German, Chinese and Japanese to English, extract subject-verb-object from raw texts (1 & 2), and ELI5 complex medical concepts. GPT-3 excels at all these tasks with a unified API. Its few-shot or even zero-shot performance can rival those of dedicated models. GPT-3 is plastic: I can correct its mistakes by adding them to the header prompt, and it will avoid the same errors in the future. In summary, GPT-3 cuts my development and learning time substantially.
However, GPT-3 is neither cheap nor universally accessible. GPT-3 costs $0.06 for 1000 tokens (about 750 words). But the devil is in the details: not only the output tokens, but those header tokens in the prompt find their way into your bill, too. You can quickly rack up a huge bill, especially when you are generating long texts. Furthermore, GPT-3 is currently not available in some countries, for example, China and Hong Kong.
Fortunately, the open-source GPT-J comes to our rescue. Compared to the large GPT-3 (175 billion parameters), the current release of GPT-J contains only 6 billion parameters (hence the name GPT-J-6B, but I will abbreviate the name to…
